Using uv projects on a network share

The wondeful uv has a strong preference for virtual environments that are placed within a project tree rather than kept centrally a la conda. One unfortunate consequence of this is for projects stored on network shares, for us usually data analysis scripts and Jupyter/marimo notebooks for visualisation and as dashboards. Simply uv adding numpy alone will dump heaps of tiny files into the folder and completely overwhelm our network share (normally OneDrive since we get 1 TB free as part of 365).

A little trick to avoid this situation, while still being able to use pyproject.toml to specify dependencies via uv. Here it goes.

1. uv init --bare to initialise your pyproject.toml if it doesn’t already exist.
2. uv add --no-sync <dependencies>, the key is --no-sync so uv doesn’t make a .venv folder and install packages there.
3. uvx --with-requirements pyproject.toml <program that you want to run>. Here are a few examples:
   • uvx --with-requirements pyproject.toml marimo edit
   • uvx --with-requirements pyproject.toml jupyter lab
   • uvx --with-requirements pyproject.toml ipython
   • uvx --with-requirements pyproject.toml python script.py

You might be tempted to run uv run script.py. Don’t! That’s going to create a virtual environment in the project folder. Either use the last example above or the nifty --isolated flag: uv run --isolated script.py.

And just like that, the most frustration-free Python workflow that I am aware of.